This model is a converted version of mkenfenheuer/whisper-small-de converted to ctranslate2 with int8 quantization.
Whisper Small DE - Maximilian Kenfenheuer
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1231
- Wer: 7.5440
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1911 | 0.25 | 1000 | 0.1567 | 9.4088 |
| 0.1959 | 0.5 | 2000 | 0.1382 | 8.5261 |
| 0.1843 | 0.75 | 3000 | 0.1285 | 7.8513 |
| 0.2134 | 1.0 | 4000 | 0.1231 | 7.5440 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0